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webcompat/webcompat.com | c3504dffec29b14eaa62ef01aa1ba78f9c2b12ef | webcompat/templates/__init__.py | python | get_description | (body_html) | Get the description of the body by parsing its content.
In cases where this fails (in case someone doesn't use the form, and
files and issue directly on GitHub and edits the template), return
something sensible. | Get the description of the body by parsing its content. | [
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"""Get the description of the body by parsing its content.
In cases where this fails (in case someone doesn't use the form, and
files and issue directly on GitHub and edits the template), return
something sensible.
"""
stripped_body = Markup.striptags(body_html)
description = re.search(r'Description: (.+?) Steps', stripped_body)
if description:
return description.group(1)[0:74]
else:
return None | [
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cloudlinux/kuberdock-platform | 8b3923c19755f3868e4142b62578d9b9857d2704 | node_storage_manage/storage.py | python | init_kd_zpool | (devices) | Creates and mounts Kuberdock zpool. | Creates and mounts Kuberdock zpool. | [
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"""Creates and mounts Kuberdock zpool."""
err_code, output = get_subprocess_result(
['zpool', 'create', '-f', KD_ZPOOL_NAME] + devices
)
raise_cmd_error(err_code, output)
err_code, output = get_subprocess_result(
['zfs', 'set', 'mountpoint={}'.format(LOCAL_STORAGE_MOUNT_POINT),
KD_ZPOOL_NAME]
)
raise_cmd_error(err_code, output)
# Default recordsize is 128k. It is too large for supposed load type.
# We want provide best performance for DB engines. Most of the apps use
# mysql with Innodb engine which have 16k page size. MyIsam and Postgresql
# have 8k page size which is also closer to 16k, than to 128k.
# Above DB page sizes (16k, 8k) are default values.
# More flexible (but more complicated) way - set recordsize for each PV,
# depending of particular application.
err_code, output = get_subprocess_result(
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owtf/owtf | 22d6d35fb2a232fcc56bf5ed504ec52fd65f15b6 | owtf/managers/target.py | python | get_all_targets | (session, key) | return results | Get all targets by key
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:type key: `str`
:return:
:rtype:
"""
results = session.query(getattr(Target, key.lower())).all()
results = [result[0] for result in results]
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LumaPictures/pymel | fa88a3f4fa18e09bb8aa9bdf4dab53d984bada72 | pymel/core/windows.py | python | lsUI | (**kwargs) | return [uitypes.PyUI(x) for x in _lsUI(**kwargs)] | Modified:
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"""
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from . import uitypes
return [uitypes.PyUI(x) for x in _lsUI(**kwargs)] | [
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mitre/multiscanner | 86e0145ba3c4a34611f257dc78cd2482ed6358db | multiscanner/common/stix2_generator/__init__.py | python | extract_http_requests_cuckoo | (signature, custom_labels=None) | return indicators | Process Cuckoo http signatures obtained from analysis.
Args:
signature: A dict from the "signatures" list from the "Cuckoo Sandbox"
portion of the report.
custom_labels: A list of labels to attach into generated Indicators.
Returns:
list: Containing ``stix2.Indicator`` with a pattern that matches the
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'''
Process Cuckoo http signatures obtained from analysis.
Args:
signature: A dict from the "signatures" list from the "Cuckoo Sandbox"
portion of the report.
custom_labels: A list of labels to attach into generated Indicators.
Returns:
list: Containing ``stix2.Indicator`` with a pattern that matches the
file by name or a variety of hashes.
'''
indicators = []
labels = ['url-watchlist']
if custom_labels:
labels.extend(custom_labels)
for ioc_mark in signature.get('marks', []):
ioc = ioc_mark.get('ioc', '')
if ioc:
url_value = ioc.split()
if len(url_value) > 1:
url_value = url_value[1]
else:
url_value = url_value[0]
ioc_pattern = create_stix2_observation_expression(
create_stix2_comparison_expression('url:value', '=', url_value)
)
indicators.append(v20.Indicator(**{
'labels': labels,
'pattern': ioc_pattern
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return indicators | [
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xjsender/haoide | 717dd706db1169bfc41e818ac6fc6cd9a0aef12d | requests/packages/urllib3/connectionpool.py | python | HTTPConnectionPool.is_same_host | (self, url) | return (scheme, host, port) == (self.scheme, self.host, self.port) | Check if the given ``url`` is a member of the same host as this
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"""
Check if the given ``url`` is a member of the same host as this
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"""
if url.startswith('/'):
return True
# TODO: Add optional support for socket.gethostbyname checking.
scheme, host, port = get_host(url)
# Use explicit default port for comparison when none is given
if self.port and not port:
port = port_by_scheme.get(scheme)
elif not self.port and port == port_by_scheme.get(scheme):
port = None
return (scheme, host, port) == (self.scheme, self.host, self.port) | [
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chribsen/simple-machine-learning-examples | dc94e52a4cebdc8bb959ff88b81ff8cfeca25022 | venv/lib/python2.7/site-packages/scipy/odr/odrpack.py | python | Data.set_meta | (self, **kwds) | Update the metadata dictionary with the keywords and data provided
by keywords.
Examples
--------
::
data.set_meta(lab="Ph 7; Lab 26", title="Ag110 + Ag108 Decay") | Update the metadata dictionary with the keywords and data provided
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""" Update the metadata dictionary with the keywords and data provided
by keywords.
Examples
--------
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data.set_meta(lab="Ph 7; Lab 26", title="Ag110 + Ag108 Decay")
"""
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sahana/eden | 1696fa50e90ce967df69f66b571af45356cc18da | modules/templates/IFRC/parser.py | python | S3Parser._parse_value | (text, fieldname) | return result | Parse a value from a piece of text | Parse a value from a piece of text | [
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"""
Parse a value from a piece of text
"""
parts = text.split(":%s:" % fieldname, 1)
parts = parts[1].split(":", 1)
result = parts[0]
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home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/components/xiaomi_tv/media_player.py | python | XiaomiTV.volume_up | (self) | Increase volume by one. | Increase volume by one. | [
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"""Increase volume by one."""
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feincms/feincms | be35576fa86083a969ae56aaf848173d1a5a3c5d | feincms/module/page/modeladmins.py | python | PageAdmin.is_visible_admin | (self, page) | return tree_editor.ajax_editable_boolean_cell(page, "active") | Instead of just showing an on/off boolean, also indicate whether this
page is not visible because of publishing dates or inherited status. | Instead of just showing an on/off boolean, also indicate whether this
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"""
Instead of just showing an on/off boolean, also indicate whether this
page is not visible because of publishing dates or inherited status.
"""
if page.parent_id and page.parent_id not in _local.visible_pages:
# parent page's invisibility is inherited
if page.id in _local.visible_pages:
_local.visible_pages.remove(page.id)
return tree_editor.ajax_editable_boolean_cell(
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)
if page.active and page.id not in _local.visible_pages:
# is active but should not be shown, so visibility limited by
# extension: show a "not active"
return tree_editor.ajax_editable_boolean_cell(
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return tree_editor.ajax_editable_boolean_cell(page, "active") | [
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F8LEFT/DecLLVM | d38e45e3d0dd35634adae1d0cf7f96f3bd96e74c | python/idaapi.py | python | ctree_anchor_t.is_citem_anchor | (self, *args) | return _idaapi.ctree_anchor_t_is_citem_anchor(self, *args) | is_citem_anchor(self) -> bool | is_citem_anchor(self) -> bool | [
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is_citem_anchor(self) -> bool
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openstack/glance | 502fa0ffc8970c087c5924742231812c0da6a114 | glance/api/v2/cached_images.py | python | CacheController.queue_image | (self, req, image_id) | PUT /queued_images/<IMAGE_ID>
Queues an image for caching. We do not check to see if
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"""
PUT /queued_images/<IMAGE_ID>
Queues an image for caching. We do not check to see if
the image is in the registry here. That is done by the
prefetcher...
"""
self._enforce(req)
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bnpy/bnpy | d5b311e8f58ccd98477f4a0c8a4d4982e3fca424 | bnpy/obsmodel/MultObsModel.py | python | MultObsModel.calcLogSoftEvMatrix_FromPost | (self, Data, **kwargs) | Calculate expected log soft ev matrix under Post.
Returns
------
L : 2D array, size N x K | Calculate expected log soft ev matrix under Post. | [
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Returns
------
L : 2D array, size N x K
'''
ElogphiT = self.GetCached('E_logphiT', 'all') # V x K
doSparse1 = 'activeonlyLP' in kwargs and kwargs['activeonlyLP'] == 2
doSparse2 = 'nnzPerRowLP' in kwargs and \
kwargs['nnzPerRowLP'] > 0 and kwargs['nnzPerRowLP'] < self.K
if doSparse2 and doSparse1:
return dict(ElogphiT=ElogphiT)
else:
E_log_soft_ev = calcLogSoftEvMatrix_FromPost_Static(
Data,
DataAtomType=self.DataAtomType,
ElogphiT=ElogphiT, **kwargs)
return dict(E_log_soft_ev=E_log_soft_ev, ElogphiT=ElogphiT) | [
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SavinaRoja/PyUserInput | 8a93a4e32430fd9da68590897e06e0be9a2ad26e | pykeyboard/windows.py | python | PyKeyboardEvent.toggle_shift_state | (self) | Does toggling for the shift state. | Does toggling for the shift state. | [
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1040003585/WebScrapingWithPython | a770fa5b03894076c8c9539b1ffff34424ffc016 | portia_examle/lib/python2.7/site-packages/pip/utils/packaging.py | python | check_requires_python | (requires_python) | return python_version in requires_python_specifier | Check if the python version in use match the `requires_python` specifier.
Returns `True` if the version of python in use matches the requirement.
Returns `False` if the version of python in use does not matches the
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Check if the python version in use match the `requires_python` specifier.
Returns `True` if the version of python in use matches the requirement.
Returns `False` if the version of python in use does not matches the
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Raises an InvalidSpecifier if `requires_python` have an invalid format.
"""
if requires_python is None:
# The package provides no information
return True
requires_python_specifier = specifiers.SpecifierSet(requires_python)
# We only use major.minor.micro
python_version = version.parse('.'.join(map(str, sys.version_info[:3])))
return python_version in requires_python_specifier | [
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p2pool/p2pool | 53c438bbada06b9d4a9a465bc13f7694a7a322b7 | nattraverso/portmapper.py | python | get_port_mapper | (proto="TCP") | return nattraverso.pynupnp.get_port_mapper() | Returns a L{NATMapper} instance, suited to map a port for
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@param proto: The protocol: 'TCP' or 'UDP'
@type proto: string
@return: A deferred called with a L{NATMapper} instance
@rtype: L{twisted.internet.defer.Deferred} | Returns a L{NATMapper} instance, suited to map a port for
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the given protocol. Defaults to TCP.
For the moment, only upnp mapper is available. It accepts both UDP and TCP.
@param proto: The protocol: 'TCP' or 'UDP'
@type proto: string
@return: A deferred called with a L{NATMapper} instance
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return nattraverso.pynupnp.get_port_mapper() | [
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openhatch/oh-mainline | ce29352a034e1223141dcc2f317030bbc3359a51 | vendor/packages/gdata/src/gdata/youtube/client.py | python | YouTubeClient.delete_track | (self, video_id, track, client_id, developer_key,
auth_token=None, **kwargs) | return self.request(http_request=http_request, **kwargs) | Deletes a track. | Deletes a track. | [
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] | def delete_track(self, video_id, track, client_id, developer_key,
auth_token=None, **kwargs):
"""Deletes a track."""
if isinstance(track, gdata.youtube.data.TrackEntry):
track_id_text_node = track.get_id().split(':')
track_id = track_id_text_node[3]
else:
track_id = track
uri = YOUTUBE_CAPTION_URI % (video_id, track_id)
http_request = atom.http_core.HttpRequest(uri = uri, method = 'DELETE')
dev_key = 'key=' + developer_key
authsub = 'AuthSub token="' + str(auth_token) + '"'
http_request.headers = {
'Authorization': authsub,
'GData-Version': self.api_version,
'X-GData-Client': client_id,
'X-GData-Key': dev_key
}
return self.request(http_request=http_request, **kwargs) | [
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F8LEFT/DecLLVM | d38e45e3d0dd35634adae1d0cf7f96f3bd96e74c | python/idaapi.py | python | get_demangled_name | (*args) | return _idaapi.get_demangled_name(*args) | get_demangled_name(frm, ea, inhibitor, demform, strict) -> char * | get_demangled_name(frm, ea, inhibitor, demform, strict) -> char * | [
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"""
get_demangled_name(frm, ea, inhibitor, demform, strict) -> char *
"""
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FabriceSalvaire/CodeReview | c48433467ac2a9a14b9c9026734f8c494af4aa95 | CodeReview/GUI/DiffViewer/DiffWidget.py | python | DiffViewerCursor.end | (self) | Insert a block and set the y positions. | Insert a block and set the y positions. | [
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"""Insert a block and set the y positions."""
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self._text_blocks[-1].y_bottom = self.y()
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canonical/cloud-init | dc1aabfca851e520693c05322f724bd102c76364 | cloudinit/analyze/__main__.py | python | configure_io | (args) | return (infh, outfh) | Common parsing and setup of input/output files | Common parsing and setup of input/output files | [
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"""Common parsing and setup of input/output files"""
if args.infile == "-":
infh = sys.stdin
else:
try:
infh = open(args.infile, "r")
except OSError:
sys.stderr.write("Cannot open file %s\n" % args.infile)
sys.exit(1)
if args.outfile == "-":
outfh = sys.stdout
else:
try:
outfh = open(args.outfile, "w")
except OSError:
sys.stderr.write("Cannot open file %s\n" % args.outfile)
sys.exit(1)
return (infh, outfh) | [
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robotlearn/pyrobolearn | 9cd7c060723fda7d2779fa255ac998c2c82b8436 | pyrobolearn/parameters/updater.py | python | ParameterUpdater.compute | (self, current=None, target=None) | return self.target | Update the target parameter(s) based on the current parameter(s).
Args:
current (int, float, torch.tensor, np.array, torch.nn.Module, None): current parameter(s). If None, it
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"""
Update the target parameter(s) based on the current parameter(s).
Args:
current (int, float, torch.tensor, np.array, torch.nn.Module, None): current parameter(s). If None, it
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Returns:
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"""
# if time to update the parameters
if (self.counter % self.sleep_count) == 0:
# if the current parameters is None, take the ones given at the initialization
if current is None:
current = self.current
if current is None:
raise ValueError("Expecting to be given current parameters, instead got None.")
# if the target is None, set it to be the current parameters.
if target is None:
target = current
# the target and current needs to be of the same type (except if current is a float or int)
if not isinstance(current, (int, float)) and type(target) != type(current):
raise TypeError("The given target and current parameters are of different types: "
"type(target)={} and type(current)={}".format(type(target), type(current)))
# inner computation
self.target = self._compute(current, target)
# increment counter
self.counter += 1
# return the new target parameter(s).
return self.target | [
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saltstack/salt | fae5bc757ad0f1716483ce7ae180b451545c2058 | salt/modules/cron.py | python | _check_instance_uid_match | (user) | return os.geteuid() == __salt__["file.user_to_uid"](user) | Returns true if running instance's UID matches the specified user UID | Returns true if running instance's UID matches the specified user UID | [
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"""
Returns true if running instance's UID matches the specified user UID
"""
return os.geteuid() == __salt__["file.user_to_uid"](user) | [
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graphcore/examples | 46d2b7687b829778369fc6328170a7b14761e5c6 | applications/popart/deep_voice/text_utils.py | python | text_to_sequence | (text, replace_prob=0.5) | return sequence | Converts a string of text to a sequence of IDs corresponding to the symbols in the text | Converts a string of text to a sequence of IDs corresponding to the symbols in the text | [
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""" Converts a string of text to a sequence of IDs corresponding to the symbols in the text """
text = text.upper()
if replace_prob > 0.0:
text = replace_with_pronunciation(text, replace_prob)
sequence = []
while len(text):
match_result = _curly_braces_re.match(text)
if not match_result:
# no curly-brace match
sequence += _symbols_to_sequence(text)
break
sequence += _symbols_to_sequence(match_result.group(1))
# split into list of phonemes before converting to sequence
sequence += _symbols_to_sequence(match_result.group(2).split(' '))
text = match_result.group(3)
# end with EOS symbol
sequence.append(_symbol_to_id[_eos])
return sequence | [
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GNS3/gns3-gui | da8adbaa18ab60e053af2a619efd468f4c8950f3 | gns3/ports/port.py | python | Port.setLabel | (self, label) | Sets a port label.
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"""
Sets a port label.
:param label: NoteItem instance.
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self._port_label = label
if self._link and self._port_label:
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pyvista/pyvista | 012dbb95a9aae406c3cd4cd94fc8c477f871e426 | pyvista/themes.py | python | DefaultTheme.colorbar_vertical | (self) | return self._colorbar_vertical | Return or set the default parameters of a vertical colorbar.
Examples
--------
Set the default colorbar width to 0.45.
>>> import pyvista
>>> pyvista.global_theme.colorbar_vertical.width = 0.45 # doctest:+SKIP
Set the default colorbar height to 0.8.
>>> import pyvista
>>> pyvista.global_theme.colorbar_vertical.height = 0.8 # doctest:+SKIP | Return or set the default parameters of a vertical colorbar. | [
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] | def colorbar_vertical(self) -> _ColorbarConfig:
"""Return or set the default parameters of a vertical colorbar.
Examples
--------
Set the default colorbar width to 0.45.
>>> import pyvista
>>> pyvista.global_theme.colorbar_vertical.width = 0.45 # doctest:+SKIP
Set the default colorbar height to 0.8.
>>> import pyvista
>>> pyvista.global_theme.colorbar_vertical.height = 0.8 # doctest:+SKIP
"""
return self._colorbar_vertical | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/Python-2.7.9/Mac/Modules/evt/evtscan.py | python | MyScanner.makerepairinstructions | (self) | return [
([("void_ptr", "*", "InMode"), ("long", "*", "InMode")],
[("InBuffer", "*", "*")]),
([("void", "*", "OutMode"), ("long", "*", "InMode"),
("long", "*", "OutMode")],
[("VarVarOutBuffer", "*", "InOutMode")]),
([("void", "wStorage", "OutMode")],
[("NullStorage", "*", "InMode")]),
# GetKeys
([('KeyMap', 'theKeys', 'InMode')],
[('*', '*', 'OutMode')]),
# GetTicker
([('unsigned long', '*', '*')],
[('unsigned_long', '*', '*')]),
] | [] | def makerepairinstructions(self):
return [
([("void_ptr", "*", "InMode"), ("long", "*", "InMode")],
[("InBuffer", "*", "*")]),
([("void", "*", "OutMode"), ("long", "*", "InMode"),
("long", "*", "OutMode")],
[("VarVarOutBuffer", "*", "InOutMode")]),
([("void", "wStorage", "OutMode")],
[("NullStorage", "*", "InMode")]),
# GetKeys
([('KeyMap', 'theKeys', 'InMode')],
[('*', '*', 'OutMode')]),
# GetTicker
([('unsigned long', '*', '*')],
[('unsigned_long', '*', '*')]),
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skylander86/lambda-text-extractor | 6da52d077a2fc571e38bfe29c33ae68f6443cd5a | lib-linux_x64/requests/utils.py | python | prepend_scheme_if_needed | (url, new_scheme) | return urlunparse((scheme, netloc, path, params, query, fragment)) | Given a URL that may or may not have a scheme, prepend the given scheme.
Does not replace a present scheme with the one provided as an argument.
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Does not replace a present scheme with the one provided as an argument.
:rtype: str
"""
scheme, netloc, path, params, query, fragment = urlparse(url, new_scheme)
# urlparse is a finicky beast, and sometimes decides that there isn't a
# netloc present. Assume that it's being over-cautious, and switch netloc
# and path if urlparse decided there was no netloc.
if not netloc:
netloc, path = path, netloc
return urlunparse((scheme, netloc, path, params, query, fragment)) | [
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blue-oil/blueoil | 0c9160b524b17482d59ae48a0c11384f1d26dccc | blueoil/cmd/init.py | python | prompt | (question) | return answers['value'] | Execute prompt answer
Args:
question (list): list of inquirer question
Returns: string of answer | Execute prompt answer | [
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Args:
question (list): list of inquirer question
Returns: string of answer
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answers = inquirer.prompt(question)
return answers['value'] | [
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oilshell/oil | 94388e7d44a9ad879b12615f6203b38596b5a2d3 | frontend/id_kind_def.py | python | IdSpec.LexerPairs | (self, kind) | return result | [] | def LexerPairs(self, kind):
# type: (Kind_t) -> List[Tuple[bool, str, Id_t]]
result = []
for is_regex, pat, id_ in self.lexer_pairs[kind]:
result.append((is_regex, pat, id_))
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maximecb/gym-minigrid | 6116191b15aec9e09e4b48edd16f144e31b412fa | gym_minigrid/minigrid.py | python | MiniGridEnv.render | (self, mode='human', close=False, highlight=True, tile_size=TILE_PIXELS) | return img | Render the whole-grid human view | Render the whole-grid human view | [
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"""
Render the whole-grid human view
"""
if close:
if self.window:
self.window.close()
return
if mode == 'human' and not self.window:
import gym_minigrid.window
self.window = gym_minigrid.window.Window('gym_minigrid')
self.window.show(block=False)
# Compute which cells are visible to the agent
_, vis_mask = self.gen_obs_grid()
# Compute the world coordinates of the bottom-left corner
# of the agent's view area
f_vec = self.dir_vec
r_vec = self.right_vec
top_left = self.agent_pos + f_vec * (self.agent_view_size-1) - r_vec * (self.agent_view_size // 2)
# Mask of which cells to highlight
highlight_mask = np.zeros(shape=(self.width, self.height), dtype=bool)
# For each cell in the visibility mask
for vis_j in range(0, self.agent_view_size):
for vis_i in range(0, self.agent_view_size):
# If this cell is not visible, don't highlight it
if not vis_mask[vis_i, vis_j]:
continue
# Compute the world coordinates of this cell
abs_i, abs_j = top_left - (f_vec * vis_j) + (r_vec * vis_i)
if abs_i < 0 or abs_i >= self.width:
continue
if abs_j < 0 or abs_j >= self.height:
continue
# Mark this cell to be highlighted
highlight_mask[abs_i, abs_j] = True
# Render the whole grid
img = self.grid.render(
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self.agent_pos,
self.agent_dir,
highlight_mask=highlight_mask if highlight else None
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if mode == 'human':
self.window.set_caption(self.mission)
self.window.show_img(img)
return img | [
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kyuupichan/electrumx | ab9024f74a034e634a518cfbcdb1fcd911e62f00 | electrumx/server/db.py | python | DB.assert_flushed | (self, flush_data) | Asserts state is fully flushed. | Asserts state is fully flushed. | [
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peterbuga/HASS-sonoff-ewelink | ab8fef3426d0f4821def48f25205e32fe23cc59a | sonoff/__init__.py | python | SonoffDevice.get_device | (self) | return None | [] | def get_device(self):
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bigmlcom/python | 35f69d2f3121f1b3dde43495cf145d4992796ad5 | bigml/multimodel.py | python | MultiModel._generate_votes | (self, input_data, missing_strategy=LAST_PREDICTION,
unused_fields=None) | return votes | Generates a MultiVote object that contains the predictions
made by each of the models. Please note that this function
calls a _predict method which assumes input data has been
properly checked against the model fields. Only casting
to the correct type will be applied. | Generates a MultiVote object that contains the predictions
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calls a _predict method which assumes input data has been
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"""
votes = MultiVote([])
for order in range(0, len(self.models)):
model = self.models[order]
prediction_info = model._predict( \
input_data,
missing_strategy=missing_strategy, unused_fields=unused_fields)
if model.boosting is not None:
votes.boosting = True
prediction_info.update( \
{"weight": model.boosting.get("weight")})
if model.boosting.get("objective_class") is not None:
prediction_info.update( \
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votes.append(prediction_info)
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TencentCloud/tencentcloud-sdk-python | 3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2 | tencentcloud/tke/v20180525/models.py | python | PrometheusNotification.__init__ | (self) | r"""
:param Enabled: 是否启用
:type Enabled: bool
:param RepeatInterval: 收敛时间
:type RepeatInterval: str
:param TimeRangeStart: 生效起始时间
:type TimeRangeStart: str
:param TimeRangeEnd: 生效结束时间
:type TimeRangeEnd: str
:param NotifyWay: 告警通知方式。目前有SMS、EMAIL、CALL、WECHAT方式。
分别代表：短信、邮件、电话、微信
注意：此字段可能返回 null，表示取不到有效值。
:type NotifyWay: list of str
:param ReceiverGroups: 告警接收组（用户组）
注意：此字段可能返回 null，表示取不到有效值。
:type ReceiverGroups: list of int non-negative
:param PhoneNotifyOrder: 电话告警顺序。
注：NotifyWay选择CALL，采用该参数。
注意：此字段可能返回 null，表示取不到有效值。
:type PhoneNotifyOrder: list of int non-negative
:param PhoneCircleTimes: 电话告警次数。
注：NotifyWay选择CALL，采用该参数。
注意：此字段可能返回 null，表示取不到有效值。
:type PhoneCircleTimes: int
:param PhoneInnerInterval: 电话告警轮内间隔。单位：秒
注：NotifyWay选择CALL，采用该参数。
注意：此字段可能返回 null，表示取不到有效值。
:type PhoneInnerInterval: int
:param PhoneCircleInterval: 电话告警轮外间隔。单位：秒
注：NotifyWay选择CALL，采用该参数。
注意：此字段可能返回 null，表示取不到有效值。
:type PhoneCircleInterval: int
:param PhoneArriveNotice: 电话告警触达通知
注：NotifyWay选择CALL，采用该参数。
注意：此字段可能返回 null，表示取不到有效值。
:type PhoneArriveNotice: bool
:param Type: 通道类型，默认为amp，支持以下
amp
webhook
注意：此字段可能返回 null，表示取不到有效值。
:type Type: str
:param WebHook: 如果Type为webhook, 则该字段为必填项
注意：此字段可能返回 null，表示取不到有效值。
:type WebHook: str | r"""
:param Enabled: 是否启用
:type Enabled: bool
:param RepeatInterval: 收敛时间
:type RepeatInterval: str
:param TimeRangeStart: 生效起始时间
:type TimeRangeStart: str
:param TimeRangeEnd: 生效结束时间
:type TimeRangeEnd: str
:param NotifyWay: 告警通知方式。目前有SMS、EMAIL、CALL、WECHAT方式。
分别代表：短信、邮件、电话、微信
注意：此字段可能返回 null，表示取不到有效值。
:type NotifyWay: list of str
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注意：此字段可能返回 null，表示取不到有效值。
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注意：此字段可能返回 null，表示取不到有效值。
:type PhoneNotifyOrder: list of int non-negative
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注意：此字段可能返回 null，表示取不到有效值。
:type PhoneCircleTimes: int
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注意：此字段可能返回 null，表示取不到有效值。
:type PhoneInnerInterval: int
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注意：此字段可能返回 null，表示取不到有效值。
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注意：此字段可能返回 null，表示取不到有效值。
:type ReceiverGroups: list of int non-negative
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注意：此字段可能返回 null，表示取不到有效值。
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注意：此字段可能返回 null，表示取不到有效值。
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self.Enabled = None
self.RepeatInterval = None
self.TimeRangeStart = None
self.TimeRangeEnd = None
self.NotifyWay = None
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self.PhoneNotifyOrder = None
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self.WebHook = None | [
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openbmc/openbmc | 5f4109adae05f4d6925bfe960007d52f98c61086 | poky/meta/lib/oe/license.py | python | list_licenses | (licensestr) | return visitor.licenses | Simply get a list of all licenses mentioned in a license string.
Binary operators are not applied or taken into account in any way | Simply get a list of all licenses mentioned in a license string.
Binary operators are not applied or taken into account in any way | [
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"""Simply get a list of all licenses mentioned in a license string.
Binary operators are not applied or taken into account in any way"""
visitor = ListVisitor()
try:
visitor.visit_string(licensestr)
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return visitor.licenses | [
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edfungus/Crouton | ada98b3930192938a48909072b45cb84b945f875 | clients/python_clients/cf_demo_client/cf_env/lib/python2.7/site-packages/setuptools/archive_util.py | python | default_filter | (src,dst) | return dst | The default progress/filter callback; returns True for all files | The default progress/filter callback; returns True for all files | [
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"""The default progress/filter callback; returns True for all files"""
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RhinoSecurityLabs/Cloud-Security-Research | b7d14b7eb51b7dea6ea6a8978682bd9671e0e183 | AWS/s3_bucket_bruteforcer/buckethead.py | python | check_region_choice | (regions) | Check that the region passed to the script is valid. If all,
return all regions.
Args:
regions (str): Comma separated string of regions.
Returns:
list: List of AWS regions. | Check that the region passed to the script is valid. If all,
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"""
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Args:
regions (str): Comma separated string of regions.
Returns:
list: List of AWS regions.
"""
regions = [x.strip() for x in regions.split(",")]
if "all" in regions:
return S3_REGIONS
elif not all(x in S3_REGIONS for x in regions):
# Not all regions passed to program are valid, raise error.
print("Invalid option passed for -r (--regions). Regions must be one or more of the following:")
print("all, {}".format(", ".join(S3_REGIONS)))
exit(1)
else:
# Every region passed is valid!
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UniversalDependencies/tools | 74faa47086440d03e06aa26bc7a8247878737c18 | compat/argparse.py | python | FileType.__call__ | (self, string) | [] | def __call__(self, string):
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openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | ansible/roles/lib_oa_openshift/library/oc_adm_ca_server_cert.py | python | OpenShiftCLI._evacuate | (self, node=None, selector=None, pod_selector=None, dry_run=False, grace_period=None, force=False) | return self.openshift_cmd(cmd, oadm=True, output=True, output_type='raw') | perform oadm manage-node evacuate | perform oadm manage-node evacuate | [
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''' perform oadm manage-node evacuate '''
cmd = ['manage-node']
if node:
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NVIDIA/DeepLearningExamples | 589604d49e016cd9ef4525f7abcc9c7b826cfc5e | PyTorch/LanguageModeling/BART/utils/optimization.py | python | get_linear_schedule_with_warmup | (optimizer, num_warmup_steps, num_training_steps, last_epoch=-1) | return LambdaLR(optimizer, lr_lambda, last_epoch) | Create a schedule with a learning rate that decreases linearly from the initial lr set in the optimizer to 0,
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optimizer (:class:`~torch.optim.Optimizer`):
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num_training_steps (:obj:`int`):
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"""
Create a schedule with a learning rate that decreases linearly from the initial lr set in the optimizer to 0,
after a warmup period during which it increases linearly from 0 to the initial lr set in the optimizer.
Args:
optimizer (:class:`~torch.optim.Optimizer`):
The optimizer for which to schedule the learning rate.
num_warmup_steps (:obj:`int`):
The number of steps for the warmup phase.
num_training_steps (:obj:`int`):
The total number of training steps.
last_epoch (:obj:`int`, `optional`, defaults to -1):
The index of the last epoch when resuming training.
Return:
:obj:`torch.optim.lr_scheduler.LambdaLR` with the appropriate schedule.
"""
def lr_lambda(current_step: int):
if current_step < num_warmup_steps:
return float(current_step) / float(max(1, num_warmup_steps))
return max(
0.0, float(num_training_steps - current_step) / float(max(1, num_training_steps - num_warmup_steps))
)
return LambdaLR(optimizer, lr_lambda, last_epoch) | [
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Source-Python-Dev-Team/Source.Python | d0ffd8ccbd1e9923c9bc44936f20613c1c76b7fb | addons/source-python/Python3/platform.py | python | platform | (aliased=0, terse=0) | return platform | Returns a single string identifying the underlying platform
with as much useful information as possible (but no more :).
The output is intended to be human readable rather than
machine parseable. It may look different on different
platforms and this is intended.
If "aliased" is true, the function will use aliases for
various platforms that report system names which differ from
their common names, e.g. SunOS will be reported as
Solaris. The system_alias() function is used to implement
this.
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absolute minimum information needed to identify the platform. | Returns a single string identifying the underlying platform
with as much useful information as possible (but no more :). | [
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""" Returns a single string identifying the underlying platform
with as much useful information as possible (but no more :).
The output is intended to be human readable rather than
machine parseable. It may look different on different
platforms and this is intended.
If "aliased" is true, the function will use aliases for
various platforms that report system names which differ from
their common names, e.g. SunOS will be reported as
Solaris. The system_alias() function is used to implement
this.
Setting terse to true causes the function to return only the
absolute minimum information needed to identify the platform.
"""
result = _platform_cache.get((aliased, terse), None)
if result is not None:
return result
# Get uname information and then apply platform specific cosmetics
# to it...
system, node, release, version, machine, processor = uname()
if machine == processor:
processor = ''
if aliased:
system, release, version = system_alias(system, release, version)
if system == 'Windows':
# MS platforms
rel, vers, csd, ptype = win32_ver(version)
if terse:
platform = _platform(system, release)
else:
platform = _platform(system, release, version, csd)
elif system in ('Linux',):
# Linux based systems
with warnings.catch_warnings():
# see issue #1322 for more information
warnings.filterwarnings(
'ignore',
r'dist\(\) and linux_distribution\(\) '
'functions are deprecated .*',
PendingDeprecationWarning,
)
distname, distversion, distid = dist('')
if distname and not terse:
platform = _platform(system, release, machine, processor,
'with',
distname, distversion, distid)
else:
# If the distribution name is unknown check for libc vs. glibc
libcname, libcversion = libc_ver(sys.executable)
platform = _platform(system, release, machine, processor,
'with',
libcname+libcversion)
elif system == 'Java':
# Java platforms
r, v, vminfo, (os_name, os_version, os_arch) = java_ver()
if terse or not os_name:
platform = _platform(system, release, version)
else:
platform = _platform(system, release, version,
'on',
os_name, os_version, os_arch)
elif system == 'MacOS':
# MacOS platforms
if terse:
platform = _platform(system, release)
else:
platform = _platform(system, release, machine)
else:
# Generic handler
if terse:
platform = _platform(system, release)
else:
bits, linkage = architecture(sys.executable)
platform = _platform(system, release, machine,
processor, bits, linkage)
_platform_cache[(aliased, terse)] = platform
return platform | [
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donnemartin/data-science-ipython-notebooks | 5b3c00d462c6e9200315afe46d0093948621eb95 | deep-learning/keras-tutorial/deep_learning_models/imagenet_utils.py | python | preprocess_input | (x, dim_ordering='default') | return x | [] | def preprocess_input(x, dim_ordering='default'):
if dim_ordering == 'default':
dim_ordering = K.image_dim_ordering()
assert dim_ordering in {'tf', 'th'}
if dim_ordering == 'th':
x[:, 0, :, :] -= 103.939
x[:, 1, :, :] -= 116.779
x[:, 2, :, :] -= 123.68
# 'RGB'->'BGR'
x = x[:, ::-1, :, :]
else:
x[:, :, :, 0] -= 103.939
x[:, :, :, 1] -= 116.779
x[:, :, :, 2] -= 123.68
# 'RGB'->'BGR'
x = x[:, :, :, ::-1]
return x | [
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mchristopher/PokemonGo-DesktopMap | ec37575f2776ee7d64456e2a1f6b6b78830b4fe0 | app/pywin/Lib/logging/__init__.py | python | Logger._log | (self, level, msg, args, exc_info=None, extra=None) | Low-level logging routine which creates a LogRecord and then calls
all the handlers of this logger to handle the record. | Low-level logging routine which creates a LogRecord and then calls
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"""
Low-level logging routine which creates a LogRecord and then calls
all the handlers of this logger to handle the record.
"""
if _srcfile:
#IronPython doesn't track Python frames, so findCaller raises an
#exception on some versions of IronPython. We trap it here so that
#IronPython can use logging.
try:
fn, lno, func = self.findCaller()
except ValueError:
fn, lno, func = "(unknown file)", 0, "(unknown function)"
else:
fn, lno, func = "(unknown file)", 0, "(unknown function)"
if exc_info:
if not isinstance(exc_info, tuple):
exc_info = sys.exc_info()
record = self.makeRecord(self.name, level, fn, lno, msg, args, exc_info, func, extra)
self.handle(record) | [
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merenlab/anvio | 9b792e2cedc49ecb7c0bed768261595a0d87c012 | anvio/sequence.py | python | Kmerizer.get_prefix_kmer_dict | (self, kmer_size, include_full_length=True) | return kmer_dict | Get k-mers of a given size from the beginning of input sequences.
Parameters
==========
kmer_size : int
Length of the k-mers to be extracted
include_full_length : bool, True
Whether to include or ignore full-length input sequences among the hashed k-mers
Returns
=======
kmer_dict : dict
Keys are unique k-mer strings identified from the input sequences.
Values are lists of the names of input sequences containing the k-mer.
These lists are sorted in descending order of sequence length and then alphanumerically by ID. | Get k-mers of a given size from the beginning of input sequences. | [
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] | def get_prefix_kmer_dict(self, kmer_size, include_full_length=True):
"""Get k-mers of a given size from the beginning of input sequences.
Parameters
==========
kmer_size : int
Length of the k-mers to be extracted
include_full_length : bool, True
Whether to include or ignore full-length input sequences among the hashed k-mers
Returns
=======
kmer_dict : dict
Keys are unique k-mer strings identified from the input sequences.
Values are lists of the names of input sequences containing the k-mer.
These lists are sorted in descending order of sequence length and then alphanumerically by ID.
"""
kmer_dict = {}
for name, seq in zip(self.names, self.seqs):
if include_full_length:
# Include input seqs as k-mers.
if kmer_size > len(seq):
continue
elif kmer_size >= len(seq):
# Do not include input seqs as k-mers.
continue
hashed_kmer = sha1(seq[: kmer_size].encode('utf-8')).hexdigest()
if hashed_kmer in kmer_dict:
kmer_dict[hashed_kmer].append((name, len(seq)))
else:
kmer_dict[hashed_kmer] = [(name, len(seq))]
for hashed_kmer, parent_seqs in kmer_dict.items():
kmer_dict[hashed_kmer] = [name for name, seq_length
in sorted(parent_seqs, key=lambda t: (-t[1], t[0]))]
return kmer_dict | [
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espnet/espnet | ea411f3f627b8f101c211e107d0ff7053344ac80 | egs/vcc20/vc1_task2/local/clean_text_finnish.py | python | g2p | (text) | return " ".join(tokens) | Convert grapheme to phoneme. | Convert grapheme to phoneme. | [
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"phoneme",
"."
] | def g2p(text):
"""Convert grapheme to phoneme."""
tokens = filter(lambda s: s != " ", f_g2p(text))
return " ".join(tokens) | [
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wxWidgets/Phoenix | b2199e299a6ca6d866aa6f3d0888499136ead9d6 | wx/lib/agw/scrolledthumbnail.py | python | ScrolledThumbnail.GetThumbBorder | (self) | return self._tBorder | Returns the thumbnail border. | Returns the thumbnail border. | [
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] | def GetThumbBorder(self):
""" Returns the thumbnail border. """
return self._tBorder | [
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euske/pdfminer | 423f851fc20ebd701bc4c8b5b7ba0e7904e18e3b | pdfminer/pdfdocument.py | python | PDFDocument.find_xref | (self, parser) | return int(prev) | Internal function used to locate the first XRef. | Internal function used to locate the first XRef. | [
"Internal",
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"used",
"to",
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] | def find_xref(self, parser):
"""Internal function used to locate the first XRef."""
# search the last xref table by scanning the file backwards.
prev = None
for line in parser.revreadlines():
line = line.strip()
if self.debug:
logging.debug('find_xref: %r' % line)
if line == b'startxref':
break
if line:
prev = line
else:
raise PDFNoValidXRef('Unexpected EOF')
if self.debug:
logging.info('xref found: pos=%r' % prev)
return int(prev) | [
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Chaffelson/nipyapi | d3b186fd701ce308c2812746d98af9120955e810 | nipyapi/nifi/models/process_group_status_snapshot_dto.py | python | ProcessGroupStatusSnapshotDTO.bytes_in | (self) | return self._bytes_in | Gets the bytes_in of this ProcessGroupStatusSnapshotDTO.
The number of bytes that have come into this ProcessGroup in the last 5 minutes
:return: The bytes_in of this ProcessGroupStatusSnapshotDTO.
:rtype: int | Gets the bytes_in of this ProcessGroupStatusSnapshotDTO.
The number of bytes that have come into this ProcessGroup in the last 5 minutes | [
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"""
Gets the bytes_in of this ProcessGroupStatusSnapshotDTO.
The number of bytes that have come into this ProcessGroup in the last 5 minutes
:return: The bytes_in of this ProcessGroupStatusSnapshotDTO.
:rtype: int
"""
return self._bytes_in | [
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grantjenks/free-python-games | 3f27c6555e2c72a9b1c668c4dd8506d7b8378d09 | freegames/pong.py | python | rectangle | (x, y, width, height) | Draw rectangle at (x, y) with given width and height. | Draw rectangle at (x, y) with given width and height. | [
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] | def rectangle(x, y, width, height):
"""Draw rectangle at (x, y) with given width and height."""
up()
goto(x, y)
down()
begin_fill()
for count in range(2):
forward(width)
left(90)
forward(height)
left(90)
end_fill() | [
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mlcommons/training | 4a4d5a0b7efe99c680306b1940749211d4238a84 | reinforcement/tensorflow/minigo/oneoffs/oneoff_utils.py | python | find_and_filter_sgf_files | (base_dir, min_year=None, komi=None) | return filtered_sgf_files | Finds all sgf files in base_dir with year >= min_year and komi | Finds all sgf files in base_dir with year >= min_year and komi | [
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] | def find_and_filter_sgf_files(base_dir, min_year=None, komi=None):
"""Finds all sgf files in base_dir with year >= min_year and komi"""
sgf_files = []
for dirpath, dirnames, filenames in os.walk(base_dir):
for filename in filenames:
if filename.endswith('.sgf'):
path = os.path.join(dirpath, filename)
sgf_files.append(path)
if min_year == komi == None:
print ("Found {} sgf_files".format(len(sgf_files)))
return sgf_files
f = filter_year_komi(min_year, komi)
filtered_sgf_files = [sgf for sgf in tqdm(sgf_files) if f(sgf)]
print("{} of {} .sgf files matched (min_year >= {}, komi = {})".format(
len(filtered_sgf_files), len(sgf_files), min_year, komi))
return filtered_sgf_files | [
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dimagi/commcare-hq | d67ff1d3b4c51fa050c19e60c3253a79d3452a39 | corehq/apps/callcenter/indicator_sets.py | python | CallCenterIndicators.date_ranges | (self) | return {
WEEK0: (weekago, self.reference_date),
WEEK1: (weekago2, weekago),
MONTH0: (daysago30, self.reference_date),
MONTH1: (daysago60, daysago30),
} | [] | def date_ranges(self):
weekago = self.reference_date - timedelta(days=7)
weekago2 = self.reference_date - timedelta(days=14)
daysago30 = self.reference_date - timedelta(days=30)
daysago60 = self.reference_date - timedelta(days=60)
return {
WEEK0: (weekago, self.reference_date),
WEEK1: (weekago2, weekago),
MONTH0: (daysago30, self.reference_date),
MONTH1: (daysago60, daysago30),
} | [
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Komodo/KomodoEdit | 61edab75dce2bdb03943b387b0608ea36f548e8e | src/udl/luddite.py | python | Shell.do_just_compile | (self, subcmd, opts, udl_path) | return commands.compile(
udl_path, output_dir=opts.output_dir,
include_path=opts.include_dirs, log=log) | ${cmd_name}: compile a .udl file into a .lexres file
${cmd_usage}
${cmd_option_list}
Note: This is a replacement for the deprecated `luddite compile'. In
a subsequent release this will get the name `luddite compile'. | ${cmd_name}: compile a .udl file into a .lexres file
${cmd_usage}
${cmd_option_list}
Note: This is a replacement for the deprecated `luddite compile'. In
a subsequent release this will get the name `luddite compile'. | [
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"""${cmd_name}: compile a .udl file into a .lexres file
${cmd_usage}
${cmd_option_list}
Note: This is a replacement for the deprecated `luddite compile'. In
a subsequent release this will get the name `luddite compile'.
"""
return commands.compile(
udl_path, output_dir=opts.output_dir,
include_path=opts.include_dirs, log=log) | [
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/ipysheet/easy.py | python | current | () | return _last_sheet | Returns the current `Sheet` instance | Returns the current `Sheet` instance | [
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OpenMined/PySyft | f181ca02d307d57bfff9477610358df1a12e3ac9 | packages/syft/src/syft/core/tensor/smpc/mpc_tensor.py | python | MPCTensor.sanity_checks | (mpc_tensor: MPCTensor, other: Any) | return mpc_tensor, other | Performs sanity checks to share data to whole superset of parites involved.
Args:
mpc_tensor(MPCTensor): input MPCTensor to perform sanity check on.
other (Any): input operand.
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mpc_tensor(MPCTensor): input MPCTensor to perform sanity check on.
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raise ValueError("The input tensor pointer should have public shape.")
if client not in parties:
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new_parties += parties
mpc_tensor = MPCTensor.reshare(mpc_tensor, new_parties)
other = MPCTensor(secret=other, parties=new_parties, shape=public_shape)
elif isinstance(other, MPCTensor):
p1 = set(mpc_tensor.parties) # parties in first MPCTensor
p2 = set(other.parties) # parties in second MPCTensor.
if p1 != p2:
parties_union = p1.union(p2)
mpc_tensor = (
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kedro-org/kedro | e78990c6b606a27830f0d502afa0f639c0830950 | kedro/framework/hooks/specs.py | python | DatasetSpecs.after_dataset_loaded | (self, dataset_name: str, data: Any) | Hook to be invoked after a dataset is loaded from the catalog.
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dataset_name: name of the dataset that was loaded from the catalog.
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enthought/traits | d22ce1f096e2a6f87c78d7f1bb5bf0abab1a18ff | traits/trait_types.py | python | List.create_editor | (self) | return list_editor(self, self) | Returns the default UI editor for the trait. | Returns the default UI editor for the trait. | [
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pyrocko/pyrocko | b6baefb7540fb7fce6ed9b856ec0c413961a4320 | src/dataset/gshhg.py | python | Polygon.__init__ | (self, gshhg_file, offset, *attr) | Initialise a GSHHG polygon
:param gshhg_file: GSHHG binary file
:type gshhg_file: str
:param offset: This polygon's offset in binary file
:type offset: int
:param attr: Polygon attributes
``(pid, npoints, _flag, west, east, south, north,
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See :file:`gshhg.h` for details.
:type attr: tuple | Initialise a GSHHG polygon | [
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'''
Initialise a GSHHG polygon
:param gshhg_file: GSHHG binary file
:type gshhg_file: str
:param offset: This polygon's offset in binary file
:type offset: int
:param attr: Polygon attributes
``(pid, npoints, _flag, west, east, south, north,
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See :file:`gshhg.h` for details.
:type attr: tuple
'''
(self.pid, self.npoints, self._flag,
self.west, self.east, self.south, self.north,
self.area, self.area_full, self.container, self.ancestor) = attr
self.west *= micro_deg
self.east *= micro_deg
self.south *= micro_deg
self.north *= micro_deg
self.level_no = (self._flag & 255)
self.level = self.LEVELS[self.level_no - 1]
self.version = (self._flag >> 8) & 255
cross = (self._flag >> 16) & 3
self.greenwhich_crossed = True if cross == 1 or cross == 3 else False
self.dateline_crossed = True if cross == 2 or cross == 3 else False
self.source = self.SOURCE[(self._flag >> 24) & 1]
if self.level_no >= 5:
self.source = self.SOURCE[2]
self.river = (self._flag >> 25) & 1
scale = 10.**(self._flag >> 26)
self.area /= scale
self.area_full /= scale
self._points = None
self._file = gshhg_file
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TarrySingh/Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials | 5bb97d7e3ffd913abddb4cfa7d78a1b4c868890e | tensorflow_dl_models/research/inception/inception/data/build_image_data.py | python | _is_png | (filename) | return filename.endswith('.png') | Determine if a file contains a PNG format image.
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filename: string, path of the image file.
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tern-tools/tern | 723f43dcaae2f2f0a08a63e5e8de3938031a386e | tern/formats/html/generator.py | python | HTML.generate_layer | (self, layer) | return report | Given a layer object, create a html report for the layer | Given a layer object, create a html report for the layer | [
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logger.debug("Creating HTML report...")
report = ""
report = report + '\n' + head_layer % (css, get_tool_version())
report = report + '\n' + report_dict_to_html(layer.to_dict())
report = report + '\n' + js
report = report + '\n' + '</body>\n</html>\n'
return report | [
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JimmXinu/FanFicFare | bc149a2deb2636320fe50a3e374af6eef8f61889 | included_dependencies/html2text/__init__.py | python | HTML2Text.replaceEntities | (self, s) | [] | def replaceEntities(self, s):
s = s.group(1)
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bikalims/bika.lims | 35e4bbdb5a3912cae0b5eb13e51097c8b0486349 | bika/lims/exportimport/instruments/resultsimport.py | python | AnalysisResultsImporter.getOverride | (self) | return self._override | If the importer must override previously entered results.
[False, False]: The results will not be overriden
[True, False]: The results will be overriden only if there's no
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[True, True]: The results will be always overriden, also if the
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cuthbertLab/music21 | bd30d4663e52955ed922c10fdf541419d8c67671 | music21/corpus/corpora.py | python | LocalCorpus.cacheFilePath | (self) | return filePath | Get the path to the file path that stores the .json file.
returns a pathlib.Path | Get the path to the file path that stores the .json file. | [
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localCorpusSettings = self._getSettings()
if localCorpusSettings is not None and localCorpusSettings.cacheFilePath is not None:
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saghul/evergreen | 22f22f45892f397c23c3e09e6ea1ad4c00b3add8 | evergreen/tasks.py | python | Task.kill | (self, typ=TaskExit, value=None, tb=None) | Terminates the current task by raising an exception into it.
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openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | openshift/installer/vendored/openshift-ansible-3.11.28-1/roles/lib_vendored_deps/library/oc_pvc.py | python | PersistentVolumeClaim.access_modes | (self) | return self._access_modes | access_modes property | access_modes property | [
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''' access_modes property '''
if self._access_modes is None:
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chapmanb/bcbb | dbfb52711f0bfcc1d26c5a5b53c9ff4f50dc0027 | biosql_ontologies/sparta.py | python | Thing.__delattr__ | (self, attr) | attr - either:
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if attr[0] == '_':
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django-import-export/django-import-export | 0d4340f02582e86d4515159becb045cad1d53ee0 | import_export/resources.py | python | Resource.before_import_row | (self, row, row_number=None, **kwargs) | Override to add additional logic. Does nothing by default. | Override to add additional logic. Does nothing by default. | [
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HymanLiuTS/flaskTs | 286648286976e85d9b9a5873632331efcafe0b21 | flasky/lib/python2.7/site-packages/sqlalchemy/sql/elements.py | python | Null._instance | (cls) | return Null() | Return a constant :class:`.Null` construct. | Return a constant :class:`.Null` construct. | [
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return Null() | [
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python/cpython | e13cdca0f5224ec4e23bdd04bb3120506964bc8b | Lib/ssl.py | python | get_server_certificate | (addr, ssl_version=PROTOCOL_TLS_CLIENT,
ca_certs=None, timeout=_GLOBAL_DEFAULT_TIMEOUT) | return DER_cert_to_PEM_cert(dercert) | Retrieve the certificate from the server at the specified address,
and return it as a PEM-encoded string.
If 'ca_certs' is specified, validate the server cert against it.
If 'ssl_version' is specified, use it in the connection attempt.
If 'timeout' is specified, use it in the connection attempt. | Retrieve the certificate from the server at the specified address,
and return it as a PEM-encoded string.
If 'ca_certs' is specified, validate the server cert against it.
If 'ssl_version' is specified, use it in the connection attempt.
If 'timeout' is specified, use it in the connection attempt. | [
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ca_certs=None, timeout=_GLOBAL_DEFAULT_TIMEOUT):
"""Retrieve the certificate from the server at the specified address,
and return it as a PEM-encoded string.
If 'ca_certs' is specified, validate the server cert against it.
If 'ssl_version' is specified, use it in the connection attempt.
If 'timeout' is specified, use it in the connection attempt.
"""
host, port = addr
if ca_certs is not None:
cert_reqs = CERT_REQUIRED
else:
cert_reqs = CERT_NONE
context = _create_stdlib_context(ssl_version,
cert_reqs=cert_reqs,
cafile=ca_certs)
with create_connection(addr, timeout=timeout) as sock:
with context.wrap_socket(sock, server_hostname=host) as sslsock:
dercert = sslsock.getpeercert(True)
return DER_cert_to_PEM_cert(dercert) | [
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/distutils/command/bdist_msi.py | python | PyDialog.__init__ | (self, *args, **kw) | Dialog(database, name, x, y, w, h, attributes, title, first,
default, cancel, bitmap=true) | Dialog(database, name, x, y, w, h, attributes, title, first,
default, cancel, bitmap=true) | [
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] | def __init__(self, *args, **kw):
"""Dialog(database, name, x, y, w, h, attributes, title, first,
default, cancel, bitmap=true)"""
Dialog.__init__(self, *args)
ruler = self.h - 36
bmwidth = 152*ruler/328
#if kw.get("bitmap", True):
# self.bitmap("Bitmap", 0, 0, bmwidth, ruler, "PythonWin")
self.line("BottomLine", 0, ruler, self.w, 0) | [
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tanghaibao/jcvi | 5e720870c0928996f8b77a38208106ff0447ccb6 | jcvi/assembly/hic.py | python | prepare_synteny | (tourfile, lastfile, odir, p, opts) | return anchorsfile, qbedfile, contig_to_beds | Prepare synteny plots for movie(). | Prepare synteny plots for movie(). | [
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] | def prepare_synteny(tourfile, lastfile, odir, p, opts):
"""
Prepare synteny plots for movie().
"""
qbedfile, sbedfile = get_bed_filenames(lastfile, p, opts)
qbedfile = op.abspath(qbedfile)
sbedfile = op.abspath(sbedfile)
qbed = Bed(qbedfile, sorted=False)
contig_to_beds = dict(qbed.sub_beds())
# Create a separate directory for the subplots and movie
mkdir(odir, overwrite=True)
os.chdir(odir)
logging.debug("Change into subdir `{}`".format(odir))
# Make anchorsfile
anchorsfile = ".".join(op.basename(lastfile).split(".", 2)[:2]) + ".anchors"
fw = open(anchorsfile, "w")
for b in Blast(lastfile):
print(
"\t".join((gene_name(b.query), gene_name(b.subject), str(int(b.score)))),
file=fw,
)
fw.close()
# Symlink sbed
symlink(sbedfile, op.basename(sbedfile))
return anchorsfile, qbedfile, contig_to_beds | [
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fooying/3102 | 0faee38c30b2e24154f41e68457cfd8f7a61c040 | thirdparty/dns/zone.py | python | Zone.to_text | (self, sorted=True, relativize=True, nl=None) | return return_value | Return a zone's text as though it were written to a file.
@param sorted: if True, the file will be written with the
names sorted in DNSSEC order from least to greatest. Otherwise
the names will be written in whatever order they happen to have
in the zone's dictionary.
@param relativize: if True, domain names in the output will be
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@type relativize: bool
@param nl: The end of line string. If not specified, the
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"""Return a zone's text as though it were written to a file.
@param sorted: if True, the file will be written with the
names sorted in DNSSEC order from least to greatest. Otherwise
the names will be written in whatever order they happen to have
in the zone's dictionary.
@param relativize: if True, domain names in the output will be
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@type relativize: bool
@param nl: The end of line string. If not specified, the
output will use the platform's native end-of-line marker (i.e.
LF on POSIX, CRLF on Windows, CR on Macintosh).
@type nl: string or None
"""
temp_buffer = StringIO()
self.to_file(temp_buffer, sorted, relativize, nl)
return_value = temp_buffer.getvalue()
temp_buffer.close()
return return_value | [
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cronyo/cronyo | cd5abab0871b68bf31b18aac934303928130a441 | cronyo/vendor/yaml/constructor.py | python | FullConstructor.construct_python_str | (self, node) | return self.construct_scalar(node) | [] | def construct_python_str(self, node):
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salabim/salabim | e0de846b042daf2dc71aaf43d8adc6486b57f376 | salabim_exp.py | python | test31 | () | [] | def test31():
class X(sim.Component):
def process(self):
yield self.hold(1)
s1.set()
yield self.hold(2)
s1.reset()
yield self.hold(2)
y.print_info()
s1.trigger()
class Y(sim.Component):
def process(self):
while True:
yield self.wait(s1, (s2, "red"), (s2, "green"), s3)
yield self.hold(1.5)
env = sim.Environment(trace=True)
env.print_info()
s1 = sim.State(name="s.")
s2 = sim.State(name="s.")
s3 = sim.State(name="s.")
q = sim.Queue("q.")
x = X()
y = Y()
env.run(10)
print("value at ", env.now(), s1.get())
print(s1.value.xduration())
print(s1.value.tx())
print(env)
print(y)
print(q)
print(s1)
s1.print_info()
s2.print_info() | [
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fluentpython/example-code-2e | 80f7f84274a47579e59c29a4657691525152c9d5 | 24-class-metaprog/bulkfood/model_v7.py | python | EntityMeta.__init__ | (cls, name, bases, attr_dict) | [] | def __init__(cls, name, bases, attr_dict):
super().__init__(name, bases, attr_dict) # <1>
for key, attr in attr_dict.items(): # <2>
if isinstance(attr, Validated):
type_name = type(attr).__name__
attr.storage_name = '_{}#{}'.format(type_name, key) | [
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trevp/tlslite | cd82fadb6bb958522b7457c5ed95890283437a4f | tlslite/tlsrecordlayer.py | python | TLSRecordLayer.send | (self, s) | return len(s) | Send data to the TLS connection (socket emulation).
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] | def send(self, s):
"""Send data to the TLS connection (socket emulation).
@raise socket.error: If a socket error occurs.
"""
self.write(s)
return len(s) | [
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perone/Pyevolve | 589b6a9b92ed1fd9ef00987bf4bfe807c4a7b7e0 | pyevolve/Statistics.py | python | Statistics.asTuple | (self) | return tuple(self.internalDict.values()) | Returns the stats as a python tuple | Returns the stats as a python tuple | [
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""" Returns the stats as a python tuple """
return tuple(self.internalDict.values()) | [
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loli/medpy | 39131b94f0ab5328ab14a874229320efc2f74d98 | medpy/graphcut/graph.py | python | Graph.get_nodes | (self) | return list(range(1, self.__nodes + 1)) | r"""
Get the nodes.
Returns
-------
nodes : list
All nodes as an ordered list. | r"""
Get the nodes.
Returns
-------
nodes : list
All nodes as an ordered list. | [
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] | def get_nodes(self):
r"""
Get the nodes.
Returns
-------
nodes : list
All nodes as an ordered list.
"""
return list(range(1, self.__nodes + 1)) | [
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guildai/guildai | 1665985a3d4d788efc1a3180ca51cc417f71ca78 | guild/external/pip/_vendor/urllib3/packages/six.py | python | _SixMetaPathImporter.get_code | (self, fullname) | return None | Return None
Required, if is_package is implemented | Return None | [
"Return",
"None"
] | def get_code(self, fullname):
"""Return None
Required, if is_package is implemented"""
self.__get_module(fullname) # eventually raises ImportError
return None | [
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avrae/avrae | 6ebe46a1ec3d4dfaa2f9b18fac948325f39f87de | cogs5e/models/initiative/combatant.py | python | Combatant.on_remove | (self) | Called when the combatant is removed from combat, either through !i remove or the combat ending. | Called when the combatant is removed from combat, either through !i remove or the combat ending. | [
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] | def on_remove(self):
"""
Called when the combatant is removed from combat, either through !i remove or the combat ending.
"""
pass | [
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MrH0wl/Cloudmare | 65e5bc9888f9d362ab2abfb103ea6c1e869d67aa | thirdparty/requests/models.py | python | Response.is_permanent_redirect | (self) | return ('location' in self.headers and self.status_code in (codes.moved_permanently, codes.permanent_redirect)) | True if this Response one of the permanent versions of redirect. | True if this Response one of the permanent versions of redirect. | [
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] | def is_permanent_redirect(self):
"""True if this Response one of the permanent versions of redirect."""
return ('location' in self.headers and self.status_code in (codes.moved_permanently, codes.permanent_redirect)) | [
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blackye/webdirdig | 11eb3df84d228127dde1dd4afcb922f5075903a2 | thirdparty_libs/requests/cookies.py | python | MockRequest.origin_req_host | (self) | return self.get_origin_req_host() | [] | def origin_req_host(self):
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hydroshare/hydroshare | 7ba563b55412f283047fb3ef6da367d41dec58c6 | hs_tracking/management/commands/stats.py | python | Command.monthly_orgs_counts | (self, start_date, end_date) | [] | def monthly_orgs_counts(self, start_date, end_date):
profiles = UserProfile.objects.filter(user__date_joined__lte=end_date)
org_count = profiles.values('organization').distinct().count()
self.print_var("monthly_orgs_counts", org_count, (start_date, end_date)) | [
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PaddlePaddle/PaddleX | 2bab73f81ab54e328204e7871e6ae4a82e719f5d | paddlex/ppcls/arch/backbone/legendary_models/hrnet.py | python | HighResolutionModule.__init__ | (self, num_filters, has_se=False) | [] | def __init__(self, num_filters, has_se=False):
super().__init__()
self.basic_block_list = nn.LayerList()
for i in range(len(num_filters)):
self.basic_block_list.append(
nn.Sequential(*[
BasicBlock(
num_channels=num_filters[i],
num_filters=num_filters[i],
has_se=has_se) for j in range(4)
]))
self.fuse_func = FuseLayers(
in_channels=num_filters, out_channels=num_filters) | [
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pybuilder/pybuilder | 12ea2f54e04f97daada375dc3309a3f525f1b5e1 | src/main/python/pybuilder/_vendor/pkg_resources/_vendor/pyparsing.py | python | ParserElement.runTests | (self, tests, parseAll=True, comment='#', fullDump=True, printResults=True, failureTests=False) | return success, allResults | Execute the parse expression on a series of test strings, showing each
test, the parsed results or where the parse failed. Quick and easy way to
run a parse expression against a list of sample strings.
Parameters:
- tests - a list of separate test strings, or a multiline string of test strings
- parseAll - (default=C{True}) - flag to pass to C{L{parseString}} when running tests
- comment - (default=C{'#'}) - expression for indicating embedded comments in the test
string; pass None to disable comment filtering
- fullDump - (default=C{True}) - dump results as list followed by results names in nested outline;
if False, only dump nested list
- printResults - (default=C{True}) prints test output to stdout
- failureTests - (default=C{False}) indicates if these tests are expected to fail parsing
Returns: a (success, results) tuple, where success indicates that all tests succeeded
(or failed if C{failureTests} is True), and the results contain a list of lines of each
test's output
Example::
number_expr = pyparsing_common.number.copy()
result = number_expr.runTests('''
# unsigned integer
100
# negative integer
-100
# float with scientific notation
6.02e23
# integer with scientific notation
1e-12
''')
print("Success" if result[0] else "Failed!")
result = number_expr.runTests('''
# stray character
100Z
# missing leading digit before '.'
-.100
# too many '.'
3.14.159
''', failureTests=True)
print("Success" if result[0] else "Failed!")
prints::
# unsigned integer
100
[100]
# negative integer
-100
[-100]
# float with scientific notation
6.02e23
[6.02e+23]
# integer with scientific notation
1e-12
[1e-12]
Success
# stray character
100Z
^
FAIL: Expected end of text (at char 3), (line:1, col:4)
# missing leading digit before '.'
-.100
^
FAIL: Expected {real number with scientific notation | real number | signed integer} (at char 0), (line:1, col:1)
# too many '.'
3.14.159
^
FAIL: Expected end of text (at char 4), (line:1, col:5)
Success
Each test string must be on a single line. If you want to test a string that spans multiple
lines, create a test like this::
expr.runTest(r"this is a test\\n of strings that spans \\n 3 lines")
(Note that this is a raw string literal, you must include the leading 'r'.) | Execute the parse expression on a series of test strings, showing each
test, the parsed results or where the parse failed. Quick and easy way to
run a parse expression against a list of sample strings.
Parameters:
- tests - a list of separate test strings, or a multiline string of test strings
- parseAll - (default=C{True}) - flag to pass to C{L{parseString}} when running tests
- comment - (default=C{'#'}) - expression for indicating embedded comments in the test
string; pass None to disable comment filtering
- fullDump - (default=C{True}) - dump results as list followed by results names in nested outline;
if False, only dump nested list
- printResults - (default=C{True}) prints test output to stdout
- failureTests - (default=C{False}) indicates if these tests are expected to fail parsing | [
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"""
Execute the parse expression on a series of test strings, showing each
test, the parsed results or where the parse failed. Quick and easy way to
run a parse expression against a list of sample strings.
Parameters:
- tests - a list of separate test strings, or a multiline string of test strings
- parseAll - (default=C{True}) - flag to pass to C{L{parseString}} when running tests
- comment - (default=C{'#'}) - expression for indicating embedded comments in the test
string; pass None to disable comment filtering
- fullDump - (default=C{True}) - dump results as list followed by results names in nested outline;
if False, only dump nested list
- printResults - (default=C{True}) prints test output to stdout
- failureTests - (default=C{False}) indicates if these tests are expected to fail parsing
Returns: a (success, results) tuple, where success indicates that all tests succeeded
(or failed if C{failureTests} is True), and the results contain a list of lines of each
test's output
Example::
number_expr = pyparsing_common.number.copy()
result = number_expr.runTests('''
# unsigned integer
100
# negative integer
-100
# float with scientific notation
6.02e23
# integer with scientific notation
1e-12
''')
print("Success" if result[0] else "Failed!")
result = number_expr.runTests('''
# stray character
100Z
# missing leading digit before '.'
-.100
# too many '.'
3.14.159
''', failureTests=True)
print("Success" if result[0] else "Failed!")
prints::
# unsigned integer
100
[100]
# negative integer
-100
[-100]
# float with scientific notation
6.02e23
[6.02e+23]
# integer with scientific notation
1e-12
[1e-12]
Success
# stray character
100Z
^
FAIL: Expected end of text (at char 3), (line:1, col:4)
# missing leading digit before '.'
-.100
^
FAIL: Expected {real number with scientific notation | real number | signed integer} (at char 0), (line:1, col:1)
# too many '.'
3.14.159
^
FAIL: Expected end of text (at char 4), (line:1, col:5)
Success
Each test string must be on a single line. If you want to test a string that spans multiple
lines, create a test like this::
expr.runTest(r"this is a test\\n of strings that spans \\n 3 lines")
(Note that this is a raw string literal, you must include the leading 'r'.)
"""
if isinstance(tests, basestring):
tests = list(map(str.strip, tests.rstrip().splitlines()))
if isinstance(comment, basestring):
comment = Literal(comment)
allResults = []
comments = []
success = True
for t in tests:
if comment is not None and comment.matches(t, False) or comments and not t:
comments.append(t)
continue
if not t:
continue
out = ['\n'.join(comments), t]
comments = []
try:
t = t.replace(r'\n','\n')
result = self.parseString(t, parseAll=parseAll)
out.append(result.dump(full=fullDump))
success = success and not failureTests
except ParseBaseException as pe:
fatal = "(FATAL)" if isinstance(pe, ParseFatalException) else ""
if '\n' in t:
out.append(line(pe.loc, t))
out.append(' '*(col(pe.loc,t)-1) + '^' + fatal)
else:
out.append(' '*pe.loc + '^' + fatal)
out.append("FAIL: " + str(pe))
success = success and failureTests
result = pe
except Exception as exc:
out.append("FAIL-EXCEPTION: " + str(exc))
success = success and failureTests
result = exc
if printResults:
if fullDump:
out.append('')
print('\n'.join(out))
allResults.append((t, result))
return success, allResults | [
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CGATOxford/cgat | 326aad4694bdfae8ddc194171bb5d73911243947 | CGAT/TreeTools.py | python | TreeDFS | (tree, node_id,
pre_function=Nop,
descend_condition=Nop,
post_function=Nop) | BFS tree tree traversal starting at node_id.
Apply functions pre_function at first and
post_function at last visit of a node. | BFS tree tree traversal starting at node_id. | [
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] | def TreeDFS(tree, node_id,
pre_function=Nop,
descend_condition=Nop,
post_function=Nop):
"""BFS tree tree traversal starting at node_id.
Apply functions pre_function at first and
post_function at last visit of a node.
"""
pre_function(node_id)
for n in tree.node(node_id).succ:
if descend_condition(node_id):
TreeDFS(tree, n, pre_function, descend_condition, post_function)
post_function(node_id) | [
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... | https://github.com/CGATOxford/cgat/blob/326aad4694bdfae8ddc194171bb5d73911243947/CGAT/TreeTools.py#L525-L538 | ||
tomplus/kubernetes_asyncio | f028cc793e3a2c519be6a52a49fb77ff0b014c9b | kubernetes_asyncio/client/models/v1beta1_certificate_signing_request.py | python | V1beta1CertificateSigningRequest.__ne__ | (self, other) | return self.to_dict() != other.to_dict() | Returns true if both objects are not equal | Returns true if both objects are not equal | [
"Returns",
"true",
"if",
"both",
"objects",
"are",
"not",
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] | def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1beta1CertificateSigningRequest):
return True
return self.to_dict() != other.to_dict() | [
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phantomcyber/playbooks | 9e850ecc44cb98c5dde53784744213a1ed5799bd | excessive_account_lockouts_enrichment_and_response.py | python | query_endpoint_rights | (action=None, success=None, container=None, results=None, handle=None, filtered_artifacts=None, filtered_results=None, custom_function=None, **kwargs) | return | [] | def query_endpoint_rights(action=None, success=None, container=None, results=None, handle=None, filtered_artifacts=None, filtered_results=None, custom_function=None, **kwargs):
phantom.debug('query_endpoint_rights() called')
# collect data for 'query_endpoint_rights' call
formatted_data_1 = phantom.get_format_data(name='endpoint_rights_mod')
parameters = []
# build parameters list for 'query_endpoint_rights' call
parameters.append({
'query': formatted_data_1,
'command': "",
'display': "",
'parse_only': "",
})
phantom.act(action="run query", parameters=parameters, assets=['splunk'], callback=join_add_comment_2, name="query_endpoint_rights")
return | [
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menpo/menpofit | 5f2f45bab26df206d43292fd32d19cd8f62f0443 | menpofit/math/regression.py | python | OptimalLinearRegression.predict | (self, x) | return np.dot(x, self.R) | r"""
Makes a prediction using the trained regression model.
Parameters
----------
x : ``(n_features,)`` `ndarray`
The input feature vector.
Returns
-------
prediction : ``(n_dims,)`` `ndarray`
The prediction vector. | r"""
Makes a prediction using the trained regression model. | [
"r",
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"prediction",
"using",
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"trained",
"regression",
"model",
"."
] | def predict(self, x):
r"""
Makes a prediction using the trained regression model.
Parameters
----------
x : ``(n_features,)`` `ndarray`
The input feature vector.
Returns
-------
prediction : ``(n_dims,)`` `ndarray`
The prediction vector.
"""
if self.bias:
if len(x.shape) == 1:
x = np.hstack((x, np.ones(1)))
else:
x = np.hstack((x, np.ones((x.shape[0], 1))))
return np.dot(x, self.R) | [
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robotlearn/pyrobolearn | 9cd7c060723fda7d2779fa255ac998c2c82b8436 | pyrobolearn/tools/bridges/mouse_keyboard/bridge_mousekeyboard_wheeled.py | python | BridgeMouseKeyboardWheeledRobot.simulator | (self) | return self._robot.simulator | Return the simulator instance. | Return the simulator instance. | [
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] | def simulator(self):
"""Return the simulator instance."""
return self._robot.simulator | [
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bendmorris/static-python | 2e0f8c4d7ed5b359dc7d8a75b6fb37e6b6c5c473 | Lib/tkinter/__init__.py | python | Misc.winfo_reqwidth | (self) | return getint(
self.tk.call('winfo', 'reqwidth', self._w)) | Return requested width of this widget. | Return requested width of this widget. | [
"Return",
"requested",
"width",
"of",
"this",
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"."
] | def winfo_reqwidth(self):
"""Return requested width of this widget."""
return getint(
self.tk.call('winfo', 'reqwidth', self._w)) | [
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a312863063/seeprettyface-generator-yellow | c75b95b56c40036d00b35f3e140cc4a45598e077 | dnnlib/tflib/optimizer.py | python | Optimizer.apply_updates | (self) | Construct training op to update the registered variables based on their gradients. | Construct training op to update the registered variables based on their gradients. | [
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"."
] | def apply_updates(self) -> tf.Operation:
"""Construct training op to update the registered variables based on their gradients."""
tfutil.assert_tf_initialized()
assert not self._updates_applied
self._updates_applied = True
devices = list(self._dev_grads.keys())
total_grads = sum(len(grads) for grads in self._dev_grads.values())
assert len(devices) >= 1 and total_grads >= 1
ops = []
with tfutil.absolute_name_scope(self.scope):
# Cast gradients to FP32 and calculate partial sum within each device.
dev_grads = OrderedDict() # device => [(grad, var), ...]
for dev_idx, dev in enumerate(devices):
with tf.name_scope("ProcessGrads%d" % dev_idx), tf.device(dev):
sums = []
for gv in zip(*self._dev_grads[dev]):
assert all(v is gv[0][1] for g, v in gv)
g = [tf.cast(g, tf.float32) for g, v in gv]
g = g[0] if len(g) == 1 else tf.add_n(g)
sums.append((g, gv[0][1]))
dev_grads[dev] = sums
# Sum gradients across devices.
if len(devices) > 1:
with tf.name_scope("SumAcrossGPUs"), tf.device(None):
for var_idx, grad_shape in enumerate(self._grad_shapes):
g = [dev_grads[dev][var_idx][0] for dev in devices]
if np.prod(grad_shape): # nccl does not support zero-sized tensors
g = nccl_ops.all_sum(g)
for dev, gg in zip(devices, g):
dev_grads[dev][var_idx] = (gg, dev_grads[dev][var_idx][1])
# Apply updates separately on each device.
for dev_idx, (dev, grads) in enumerate(dev_grads.items()):
with tf.name_scope("ApplyGrads%d" % dev_idx), tf.device(dev):
# Scale gradients as needed.
if self.use_loss_scaling or total_grads > 1:
with tf.name_scope("Scale"):
coef = tf.constant(np.float32(1.0 / total_grads), name="coef")
coef = self.undo_loss_scaling(coef)
grads = [(g * coef, v) for g, v in grads]
# Check for overflows.
with tf.name_scope("CheckOverflow"):
grad_ok = tf.reduce_all(tf.stack([tf.reduce_all(tf.is_finite(g)) for g, v in grads]))
# Update weights and adjust loss scaling.
with tf.name_scope("UpdateWeights"):
# pylint: disable=cell-var-from-loop
opt = self._dev_opt[dev]
ls_var = self.get_loss_scaling_var(dev)
if not self.use_loss_scaling:
ops.append(tf.cond(grad_ok, lambda: opt.apply_gradients(grads), tf.no_op))
else:
ops.append(tf.cond(grad_ok,
lambda: tf.group(tf.assign_add(ls_var, self.loss_scaling_inc), opt.apply_gradients(grads)),
lambda: tf.group(tf.assign_sub(ls_var, self.loss_scaling_dec))))
# Report statistics on the last device.
if dev == devices[-1]:
with tf.name_scope("Statistics"):
ops.append(autosummary.autosummary(self.id + "/learning_rate", self.learning_rate))
ops.append(autosummary.autosummary(self.id + "/overflow_frequency", tf.where(grad_ok, 0, 1)))
if self.use_loss_scaling:
ops.append(autosummary.autosummary(self.id + "/loss_scaling_log2", ls_var))
# Initialize variables and group everything into a single op.
self.reset_optimizer_state()
tfutil.init_uninitialized_vars(list(self._dev_ls_var.values()))
return tf.group(*ops, name="TrainingOp") | [
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007gzs/dingtalk-sdk | 7979da2e259fdbc571728cae2425a04dbc65850a | dingtalk/client/api/taobao.py | python | TbALiJianKangZhuiSuMa.alibaba_alihealth_drug_code_common_list_codeinfo | (
self,
ref_ent_id,
search_source,
code_list,
auth_ref_ent_id,
cert_isv_no='',
invocation='',
terminal_type='',
terminal_name='',
bureau_name='',
error_message=''
) | return self._top_request(
"alibaba.alihealth.drug.code.common.list.codeinfo",
{
"ref_ent_id": ref_ent_id,
"search_source": search_source,
"code_list": code_list,
"auth_ref_ent_id": auth_ref_ent_id,
"cert_isv_no": cert_isv_no,
"invocation": invocation,
"terminal_type": terminal_type,
"terminal_name": terminal_name,
"bureau_name": bureau_name,
"error_message": error_message
}
) | 通用查询码接口
文档地址：https://open-doc.dingtalk.com/docs/api.htm?apiId=41299
:param ref_ent_id: 企业refEntId
:param search_source: 标示医院业务
:param code_list: 追溯码
:param auth_ref_ent_id: 验证权限企业id
:param cert_isv_no: 证件编号
:param invocation: 调用方式：formal-正式、test-测试
:param terminal_type: 终端类型 1：零售
:param terminal_name: 调用零售药店名称
:param bureau_name: 城市名称
:param error_message: 错误信息 | 通用查询码接口
文档地址：https://open-doc.dingtalk.com/docs/api.htm?apiId=41299 | [
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".",
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"/",
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"=",
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] | def alibaba_alihealth_drug_code_common_list_codeinfo(
self,
ref_ent_id,
search_source,
code_list,
auth_ref_ent_id,
cert_isv_no='',
invocation='',
terminal_type='',
terminal_name='',
bureau_name='',
error_message=''
):
"""
通用查询码接口
文档地址：https://open-doc.dingtalk.com/docs/api.htm?apiId=41299
:param ref_ent_id: 企业refEntId
:param search_source: 标示医院业务
:param code_list: 追溯码
:param auth_ref_ent_id: 验证权限企业id
:param cert_isv_no: 证件编号
:param invocation: 调用方式：formal-正式、test-测试
:param terminal_type: 终端类型 1：零售
:param terminal_name: 调用零售药店名称
:param bureau_name: 城市名称
:param error_message: 错误信息
"""
return self._top_request(
"alibaba.alihealth.drug.code.common.list.codeinfo",
{
"ref_ent_id": ref_ent_id,
"search_source": search_source,
"code_list": code_list,
"auth_ref_ent_id": auth_ref_ent_id,
"cert_isv_no": cert_isv_no,
"invocation": invocation,
"terminal_type": terminal_type,
"terminal_name": terminal_name,
"bureau_name": bureau_name,
"error_message": error_message
}
) | [
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linuxmint/mintupdate | 476059f9f977cd1d0d7a451c64931a7a9ffd4bbf | usr/lib/linuxmint/mintUpdate/mintUpdate.py | python | MintUpdate.close_preferences | (self, widget, window) | [] | def close_preferences(self, widget, window):
self.window.set_sensitive(True)
self.preferences_window_showing = False
window.destroy()
self.refresh() | [
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"refre... | https://github.com/linuxmint/mintupdate/blob/476059f9f977cd1d0d7a451c64931a7a9ffd4bbf/usr/lib/linuxmint/mintUpdate/mintUpdate.py#L2466-L2470 | ||||
cea-hpc/clustershell | c421133ed4baa69e35ff76c476d4097201485344 | lib/ClusterShell/RangeSet.py | python | RangeSetND.intersection_update | (self, other) | ``s.intersection_update(t)`` returns nodeset s keeping only
elements also found in t. | ``s.intersection_update(t)`` returns nodeset s keeping only
elements also found in t. | [
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"""
``s.intersection_update(t)`` returns nodeset s keeping only
elements also found in t.
"""
if other is self:
return
tmp_rnd = RangeSetND()
empty_rset = RangeSet()
for rgvec in self._veclist:
for ergvec in other._veclist:
irgvec = [rg.intersection(erg) \
for rg, erg in zip(rgvec, ergvec)]
if not empty_rset in irgvec:
tmp_rnd.update([irgvec])
# substitute
self.veclist = tmp_rnd.veclist | [
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robotlearn/pyrobolearn | 9cd7c060723fda7d2779fa255ac998c2c82b8436 | pyrobolearn/simulators/mujoco.py | python | Mujoco.get_joint_names | (self, body_id, joint_ids) | return names | Return the name of the given joint(s).
Args:
body_id (int): unique body id.
joint_ids (int, list[int]): a joint id, or list of joint ids.
Returns:
if 1 joint:
str: name of the joint
if multiple joints:
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"""
Return the name of the given joint(s).
Args:
body_id (int): unique body id.
joint_ids (int, list[int]): a joint id, or list of joint ids.
Returns:
if 1 joint:
str: name of the joint
if multiple joints:
str[N]: name of each joint
"""
body = self._bodies[body_id]
one_joint = isinstance(joint_ids, int)
if one_joint:
joint_ids = [joint_ids]
names = []
for joint_id in joint_ids:
name = body.joints[joint_id].name
if name.startswith('prl_'):
name = '_'.join(name.split('_')[1:-1])
names.append(name)
if one_joint and len(names) > 1:
return names[0]
return names | [
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nicola-decao/s-vae-pytorch | 671c46c0772a2c92a602252311864c48c816bc44 | examples/mnist.py | python | ModelVAE.__init__ | (self, h_dim, z_dim, activation=F.relu, distribution='normal') | ModelVAE initializer
:param h_dim: dimension of the hidden layers
:param z_dim: dimension of the latent representation
:param activation: callable activation function
:param distribution: string either `normal` or `vmf`, indicates which distribution to use | ModelVAE initializer
:param h_dim: dimension of the hidden layers
:param z_dim: dimension of the latent representation
:param activation: callable activation function
:param distribution: string either `normal` or `vmf`, indicates which distribution to use | [
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"""
ModelVAE initializer
:param h_dim: dimension of the hidden layers
:param z_dim: dimension of the latent representation
:param activation: callable activation function
:param distribution: string either `normal` or `vmf`, indicates which distribution to use
"""
super(ModelVAE, self).__init__()
self.z_dim, self.activation, self.distribution = z_dim, activation, distribution
# 2 hidden layers encoder
self.fc_e0 = nn.Linear(784, h_dim * 2)
self.fc_e1 = nn.Linear(h_dim * 2, h_dim)
if self.distribution == 'normal':
# compute mean and std of the normal distribution
self.fc_mean = nn.Linear(h_dim, z_dim)
self.fc_var = nn.Linear(h_dim, z_dim)
elif self.distribution == 'vmf':
# compute mean and concentration of the von Mises-Fisher
self.fc_mean = nn.Linear(h_dim, z_dim)
self.fc_var = nn.Linear(h_dim, 1)
else:
raise NotImplemented
# 2 hidden layers decoder
self.fc_d0 = nn.Linear(z_dim, h_dim)
self.fc_d1 = nn.Linear(h_dim, h_dim * 2)
self.fc_logits = nn.Linear(h_dim * 2, 784) | [
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... | https://github.com/nicola-decao/s-vae-pytorch/blob/671c46c0772a2c92a602252311864c48c816bc44/examples/mnist.py#L23-L53 | ||
plotly/plotly.py | cfad7862594b35965c0e000813bd7805e8494a5b | packages/python/plotly/plotly/graph_objs/scatter3d/_marker.py | python | Marker.sizemin | (self) | return self["sizemin"] | Has an effect only if `marker.size` is set to a numerical
array. Sets the minimum size (in px) of the rendered marker
points.
The 'sizemin' property is a number and may be specified as:
- An int or float in the interval [0, inf]
Returns
-------
int|float | Has an effect only if `marker.size` is set to a numerical
array. Sets the minimum size (in px) of the rendered marker
points.
The 'sizemin' property is a number and may be specified as:
- An int or float in the interval [0, inf] | [
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"""
Has an effect only if `marker.size` is set to a numerical
array. Sets the minimum size (in px) of the rendered marker
points.
The 'sizemin' property is a number and may be specified as:
- An int or float in the interval [0, inf]
Returns
-------
int|float
"""
return self["sizemin"] | [
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basho/riak-python-client | 91de13a16607cdf553d1a194e762734e3bec4231 | riak/content.py | python | RiakContent.add_link | (self, obj, tag=None) | return self._robject | add_link(obj, tag=None)
Add a link to a RiakObject.
:param obj: Either a RiakObject or 3 item link tuple consisting
of (bucket, key, tag).
:type obj: mixed
:param tag: Optional link tag. Defaults to bucket name. It is ignored
if ``obj`` is a 3 item link tuple.
:type tag: string
:rtype: :class:`RiakObject <riak.riak_object.RiakObject>` | add_link(obj, tag=None) | [
"add_link",
"(",
"obj",
"tag",
"=",
"None",
")"
] | def add_link(self, obj, tag=None):
"""
add_link(obj, tag=None)
Add a link to a RiakObject.
:param obj: Either a RiakObject or 3 item link tuple consisting
of (bucket, key, tag).
:type obj: mixed
:param tag: Optional link tag. Defaults to bucket name. It is ignored
if ``obj`` is a 3 item link tuple.
:type tag: string
:rtype: :class:`RiakObject <riak.riak_object.RiakObject>`
"""
if isinstance(obj, tuple):
newlink = obj
else:
newlink = (obj.bucket.name, obj.key, tag)
self.links.append(newlink)
return self._robject | [
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... | https://github.com/basho/riak-python-client/blob/91de13a16607cdf553d1a194e762734e3bec4231/riak/content.py#L166-L186 | |
yukitsuji/3D_CNN_tensorflow | 5104ecf3f75a4e51a2170b72244e3f2a8993ce25 | input_velodyne.py | python | filter_camera_angle | (places) | return places[bool_in] | Filter camera angles for KiTTI Datasets | Filter camera angles for KiTTI Datasets | [
"Filter",
"camera",
"angles",
"for",
"KiTTI",
"Datasets"
] | def filter_camera_angle(places):
"""Filter camera angles for KiTTI Datasets"""
bool_in = np.logical_and((places[:, 1] < places[:, 0] - 0.27), (-places[:, 1] < places[:, 0] - 0.27))
# bool_in = np.logical_and((places[:, 1] < places[:, 0]), (-places[:, 1] < places[:, 0]))
return places[bool_in] | [
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hyperledger/fabric-sdk-py | 8ee33a8981887e37950dc0f36a7ec63b3a5ba5c3 | hfc/fabric/channel/channel.py | python | Channel._build_channel_header | (type, tx_id, channel_id,
timestamp, epoch=0, extension=None) | return channel_header | Build channel.
:param extension: extension (Default value = None)
:param timestamp: timestamp
:param channel_id: channel id
:param tx_id: transaction id
:param type: type
:param epoch: epoch
:return: common_proto.Header instance (Default value = 0) | Build channel. | [
"Build",
"channel",
"."
] | def _build_channel_header(type, tx_id, channel_id,
timestamp, epoch=0, extension=None):
"""Build channel.
:param extension: extension (Default value = None)
:param timestamp: timestamp
:param channel_id: channel id
:param tx_id: transaction id
:param type: type
:param epoch: epoch
:return: common_proto.Header instance (Default value = 0)
"""
channel_header = common_pb2.ChannelHeader()
channel_header.type = type
channel_header.version = 1
channel_header.channel_id = proto_str(channel_id)
channel_header.tx_id = proto_str(tx_id)
channel_header.epoch = epoch
channel_header.timestamp = timestamp
if extension:
channel_header.extension = extension
return channel_header | [
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